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Publication details

Document type
Conference papers

Document subtype
Extended abstract/Short paper

Title
Improving the asymptotically unbiased extreme value index estimation

Participants in the publication
Frederico Caeiro (Author)
Ivanilda Cabral (Author)
Maria Ivette Gomes (Author)
Dep. Estatística e Investigação Operacional
CEAUL - Centro de Estatística e Aplicações

Scope
International

Refereeing
Yes

Editor(s)
Oliveira, T.A. et al.

Date of Publication
2016

Institution
FACULDADE DE CIÊNCIAS DA UNIVERSIDADE DE LISBOA

Event
10th Workshop on Statistics, Mathematics and Computation and 5th Portuguese-Polish Workshop on Biometry: Book of Abstracts

Publication Identifiers

Address
Lisboa, Portugal

Publisher
Universidade Aberta and CEAUL

Number of pages
1
Starting page
117
Last page
117

Document Identifiers
URL - https://www.researchgate.net/profile/Maria_Gomes17/publication/321071771_Improving_the_asymptotically_unbiased_extreme_value_index_estimation/links/5a0c07c0aca2721a23fa3fbd/Improving-the-asymptotically-unbiased-extreme-value-index-estimation.pdf


Export

APA
Frederico Caeiro, Ivanilda Cabral, Maria Ivette Gomes, (2016). Improving the asymptotically unbiased extreme value index estimation. 10th Workshop on Statistics, Mathematics and Computation and 5th Portuguese-Polish Workshop on Biometry: Book of Abstracts, 117-117

IEEE
Frederico Caeiro, Ivanilda Cabral, Maria Ivette Gomes, "Improving the asymptotically unbiased extreme value index estimation" in 10th Workshop on Statistics, Mathematics and Computation and 5th Portuguese-Polish Workshop on Biometry: Book of Abstracts, Lisboa, Portugal, 2016, pp. 117-117, doi:

BIBTEX
@InProceedings{50351, author = {Frederico Caeiro and Ivanilda Cabral and Maria Ivette Gomes}, title = {Improving the asymptotically unbiased extreme value index estimation}, booktitle = {10th Workshop on Statistics, Mathematics and Computation and 5th Portuguese-Polish Workshop on Biometry: Book of Abstracts}, year = 2016, pages = {117-117}, address = {Lisboa, Portugal}, publisher = {Universidade Aberta and CEAUL} }